The present invention is concerned generally with a system and method for carrying out an automated evaluation of sensor signals and to establish a filter function for removing serial correlation, if present, in the sensor signals. More particularly, the invention is directed to an automated methodology and system for evaluating statistical characteristics of signals from one or more sensors, designing an optimal filter for the particular type of noise characteristics and set sequential probability ratio test (SPRT) parameters so that the overall system meets prescribed false alarm and missed alarm probabilities.
A SPRT methodology has been developed (see, for example, U.S. Pat. Nos. 5,223,207; 5,459,675; and 5,410,492) for performing pattern recognition in industrial systems. The SPRT system validates signals and monitors sensor and equipment operability. Such a SPRT system can be trained to operate on signals coming from any type of sensor and with any sampling rate. Therefore, a properly trained SPRT system has defensible, quantitative false alarm and missed alarm probabilities. However, such SPRT systems require a technical specialist to customize and train the SPRT system for each new sensor configuration. Such an approach tends to be expensive and cumbersome to implement for each new application.
It is therefore an object of the invention to provide an improved method and system for pattern recognition.
It is another object of the invention to provide a novel method and system for automated tuning of a SPRT method and system.
It is also an object of the invention to provide an improved method and system for automated training of SPRT modules for a new surveillance or data monitoring application.
It is a further object of the invention to provide a novel method and system for automated adaptation and training of pattern recognition formalisms.
It is an additional object of the invention to provide an improved method and system for examining training data from a normal state with calibrated sensors, or otherwise normalized sources of data, and then employing a bootstrapping procedure to design an optimized pattern recognition methodology.
It is still a further object of the invention to provide a novel method and system for the automated design of an integrated SPRT/filter system for achieving an optimized SPRT system.